Industrial equipment data acquisition system and method

Abstract

The invention relates to the technical field of data processing, in particular to an industrial equipment data acquisition system and method. The system comprises a sensor module installed on industrial equipment and used for collecting multi-modal data of the industrial equipment; the sensor verification module is installed on industrial equipment, is electrically connected with the sensor module, and is used for carrying out initial verification on the sensor module before multi-modal data acquisition and carrying out data preliminary verification on the multi-modal data; the data transmission module is electrically connected with the sensor verification module and is used for transmitting the verification data subjected to preliminary verification to a far-end processing platform; and the data storage device is electrically connected with the sensor verification module and is used for storing verification data of preliminary data verification. The objective of the invention is to solve the problem of low data acquisition precision caused by the fact that an existing acquisition system is easily affected by an equipment production environment.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an industrial equipment data acquisition system and method. Background Art

[0002] Industrial equipment is a tangible fixed asset used by companies for long periods of time and maintained repeatedly in their original condition. Industrial equipment is directly involved in production processes, power transmission, or scientific research. Industrial equipment can be categorized by purpose, including general-purpose equipment, specialized equipment, automated equipment, and specialized equipment. For example, existing automated equipment includes CNC machine tools, assembly lines, industrial robots, and automatic feeders, which improve production efficiency and processing precision.

[0003] Currently, existing data collection systems for industrial equipment use various sensors, collection devices, or systems to acquire device information and transmit this information to a central processing system via transmission equipment. However, different protocols for different sensors in existing data collection systems make debugging inconvenient and result in low data collection efficiency. Furthermore, the proximity of the collecting sensors to the equipment being collected makes them susceptible to the effects of the equipment's production environment, resulting in low data collection accuracy.

[0004] Therefore, it is necessary to design an industrial equipment data acquisition system and method to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes an industrial equipment data acquisition system and method, aiming to solve the problem that the existing acquisition system is easily affected by the equipment production environment, resulting in low data acquisition accuracy.

[0006] In one aspect, the present invention provides an industrial equipment data acquisition system, comprising:

[0007] Sensor modules are installed on industrial equipment to collect multimodal data from the industrial equipment;

[0008] A sensor calibration module is installed on the industrial equipment and is electrically connected to the sensor module, and is used to perform an initial calibration on the sensor module before multimodal data acquisition and to perform preliminary data verification on the multimodal data;

[0009] a data transmission module, electrically connected to the sensor verification module, for transmitting the verification data of the preliminary verification to a remote processing platform;

[0010] A data storage device is electrically connected to the sensor verification module and is used to store verification data of preliminary data verification.

[0011] Furthermore, the sensor module includes a sensor unit and a data pre-processing unit, both of which are installed on the industrial equipment, and the sensor unit is electrically connected to the data pre-processing unit;

[0012] The sensor unit is used to collect multimodal initial data of industrial equipment including images, sounds, temperature and humidity, electrical signals and pressure;

[0013] The data preprocessing unit is used to preprocess the multimodal initial data to obtain multimodal data.

[0014] Furthermore, the sensor calibration module includes a first calibration unit and a second calibration unit, wherein the first calibration unit and the second calibration unit are both installed on the industrial equipment and are both electrically connected to the sensor module;

[0015] The first verification unit is provided with a preset initial verification model. After determining an initial verification coefficient in the preset initial verification model based on the acquisition time of the sensor module, the first verification unit uses the initial verification coefficient to perform initial verification on the sensor module before multimodal data acquisition;

[0016] A data comparison model is provided in the second verification unit. The second verification unit confirms data comparison parameters in the data comparison model based on an initial verification coefficient. The second verification unit performs preliminary data verification on each data in the multimodal data using the data comparison parameters.

[0017] Furthermore, the sensor calibration module further includes a calibration warning unit;

[0018] The verification warning unit is electrically connected to the first verification unit. When the first verification unit fails in initial verification, the verification warning unit issues a warning prompt and restarts the first verification unit.

[0019] Furthermore, the second verification unit is provided with a data aggregation unit;

[0020] The data summarizing unit is electrically connected to the second verification unit, and is used to summarize each initial verification result after preliminary verification of the data to obtain verification data.

[0021] Furthermore, the data transmission module includes an encryption unit and a transmission unit;

[0022] The encryption unit and the transmission unit are both electrically connected to the sensor verification module, and the encryption unit is used to encrypt the verification data of the preliminary verification;

[0023] The transmission unit is used to transmit the encrypted verification data that will be preliminarily verified to the remote processing platform.

[0024] Furthermore, the transmission module further includes a data volume monitoring unit, and the data volume monitoring unit is electrically connected to the sensor verification module;

[0025] The data volume monitoring unit is provided with a data volume threshold, and the data volume monitoring unit is used to monitor the data volume of the encrypted preliminary verified verification data;

[0026] If the monitored data volume is greater than the data volume threshold, the data volume monitoring unit sub-packets the data volume of the initially verified verification data.

[0027] Furthermore, the data storage device includes a storage unit and a retrieval unit, the storage unit is electrically connected to the sensor verification module, and the storage unit is used to store verification data of the preliminary data verification;

[0028] The retrieval unit is electrically connected to the storage unit, and is used to retrieve verification data for preliminary verification of data in the storage unit.

[0029] Furthermore, the remote processing platform includes a data processing module and an anomaly detection module;

[0030] The data processing module is electrically connected to the data transmission module, and the data processing module is used to process the verification data of the preliminary verification;

[0031] The anomaly detection module is electrically connected to the data processing module, and the anomaly detection module is used to perform anomaly monitoring on the data after data processing.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows: through the configuration of a sensor module, a sensor calibration module, a data transmission module, and a data storage device, the sensor module is used to collect multimodal data of industrial equipment, thereby being able to comprehensively monitor the working status of the industrial equipment; the sensor calibration module is used to perform an initial calibration on the sensor module before multimodal data collection and to perform preliminary data verification on the multimodal data, thereby ensuring the accuracy of the sensor baseline through the initial calibration, and at the same time, the preliminary data verification avoids invalid data transmission; the data transmission module is used to transmit the verification data of the preliminary verification to a remote processing platform, thereby processing the verification data through the remote processing platform; the data storage device is used to store the verification data of the preliminary data verification; the data storage device is used for local backup or subsequent analysis of the data. When the data transmission module is interrupted, retransmission can be performed, thereby improving the accuracy of data collection and reducing the risk of systematic data errors.

[0033] On the other hand, the present application also provides an industrial equipment data acquisition method, based on any of the above industrial equipment data acquisition systems, comprising the following steps:

[0034] Drive sensor modules to collect multimodal data from industrial equipment;

[0035] Performing an initial calibration on the sensor module before multimodal data acquisition and performing preliminary data verification on the multimodal data through the sensor calibration module to obtain an initial calibration result and preliminary verification data;

[0036] Using the data transmission module to transmit the preliminary verification data to the remote processing platform;

[0037] The verification data of the preliminary verification of the data is stored by the data storage device.

[0038] It is understandable that the above industrial equipment data acquisition system and method have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0040] Figure 1 This is a functional block diagram of an industrial equipment data acquisition system provided by an embodiment of the present invention.

[0041] Figure 2 This is a functional block diagram of another embodiment of an industrial equipment data acquisition system provided by an embodiment of the present invention.

[0042] Figure 3 The present invention provides a flowchart of an industrial equipment data collection method. DETAILED DESCRIPTION

[0043] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0044] In some embodiments of the present application, see Figure 1As shown, an industrial equipment data acquisition system includes a sensor module 110 , a sensor calibration module 120 , a data transmission module 130 and a data storage device 140 .

[0045] In this embodiment, the sensor module 110 is installed on the industrial equipment to collect multimodal data of the industrial equipment. The sensor module 110 is a physical quantity detection unit installed in the key parts of the industrial equipment, which supports multimodal data collection. The multimodal data includes temperature data, pressure data, current data, voltage data, etc. The sensor module 110 collects analog signals from the industrial equipment, converts them into digital signals through ADC, and obtains multimodal data. The sensor module 110 collects multimodal data at a fixed period, such as 10 seconds. This allows the operating status of the equipment to be captured in real time, providing raw data for predictive maintenance. At the same time, by collecting multimodal data, the accuracy of fault diagnosis can be improved.

[0046] The sensor calibration module 120 is installed on the industrial equipment and is electrically connected to the sensor module 110, and is used to perform initial calibration on the sensor module 110 before multimodal data acquisition and to perform preliminary data verification on the multimodal data. Among them, the sensor calibration module 120 performs calibration management on the sensor module 110 throughout its life cycle, which includes at least two states: initial calibration (power-on self-test) and real-time verification (running calibration); the initial calibration checks the connection status and power supply voltage of the sensor module 110 to achieve hardware self-test, and the initial calibration avoids systematic data errors caused by hardware failures. Running calibration verifies the range and accuracy through a standard signal source, such as using weights to calibrate a pressure sensor. Real-time verification filters out abnormal values, such as spike signals caused by electromagnetic interference, thereby achieving preliminary data verification of the multimodal data, generating preliminarily verified qualified multimodal data as verification data, and then being able to determine the reliability and accuracy of the multimodal data.

[0047] The data transmission module is electrically connected to the sensor verification module 120 and is used to transmit the verification data of the preliminary verification to the remote processing platform. The data transmission module is a communication unit responsible for transmitting the valid data after verification (the verification data of the preliminary verification) to the remote platform. In this embodiment, wired transmission can be performed by using Ethernet or RS485, or wireless transmission can be performed by using LoRa, 4G or 5G. By transmitting the verification data of the preliminary verification to the remote processing platform, the remote platform can realize centralized monitoring and analysis of the data. For example, the remote platform can predict equipment failures based on the preset model in the cloud to generate maintenance recommendations for industrial equipment.

[0048] The data storage device is electrically connected to the sensor verification module 120 and is used to store verification data for preliminary data verification. The data storage device is a device for locally storing verification data, and usually uses an industrial-grade SSD or SD card to store verification data.

[0049] In this embodiment, the multimodal data of the industrial equipment is collected by the sensor module 110, thereby enabling comprehensive monitoring of the working status of the industrial equipment. The sensor verification module 120 performs an initial verification on the sensor module 110 before multimodal data collection and performs preliminary data verification on the multimodal data. Through the initial verification, the accuracy of the sensor baseline is ensured. At the same time, the preliminary data verification avoids invalid data transmission. The data transmission module transmits the verification data of the preliminary verification to the remote processing platform, and the verification data is processed by the remote processing platform. The data storage device stores the verification data of the preliminary data verification. The data storage device is used for local backup or subsequent analysis of the data. The sensor verification module 120 performs abnormality detection to ensure data quality. At the same time, by storing the verification data of the preliminary data verification, the data transmission module is prevented from being interrupted and can be retransmitted, thereby improving the accuracy and precision of data collection.

[0050] Based on the above examples, see Figure 2 As shown, the sensor module 110 in this embodiment includes a sensor unit and a data preprocessing unit, both of which are installed on industrial equipment, and the sensor unit is electrically connected to the data preprocessing unit. The sensor unit is a physical quantity detection unit installed in a key part of the industrial equipment, supporting multimodal data acquisition. The data preprocessing unit is a local processing module that cleans, converts, and standardizes the multimodal initial data collected by the sensor unit. At the same time, it also reduces the complexity of the sensor module 110.

[0051] The sensor unit is used to collect multimodal initial data from industrial equipment, including images, sounds, temperature and humidity, electrical signals, and pressure. Specifically, analog signals are collected through hardware such as MEMS sensors, piezoelectric sensors, temperature and humidity sensors, cameras, and microphones. After ADC conversion, the analog signals are output as digital signals, supporting various communication protocols such as I2C, SPI, and USB. Multimodal data fusion can improve fault diagnosis accuracy.

[0052] The data preprocessing unit is used to preprocess the multimodal initial data to obtain multimodal data. Among them, the multimodal data is subjected to denoising and standardization operations by the preprocessing unit, which significantly improves the data quality and reduces the interference of subsequent analysis. Local preprocessing reduces redundant data transmission, reduces network bandwidth occupancy, and supports the dual needs of real-time monitoring and historical tracing. The multimodal data architecture supports new sensor types (such as visual and acoustic data) in the future, and the preprocessing unit can adapt to the conversion requirements of different data formats. In this embodiment, data cleaning is to identify and process missing values ​​and outliers from the multimodal initial data, such as using existing Z-score or IQR methods to detect outliers. Data conversion is to encode categorical features, such as one-hot encoding, and to bin or standardize numerical features, such as using Z-score standardization. By reducing the scale and complexity of data through preprocessing, the prediction accuracy is improved.

[0053] In this embodiment, the sensor unit collects initial multimodal data at a fixed interval. The data preprocessing unit cleans, converts, and standardizes the initial data to produce high-quality multimodal data. The preprocessed data is then synchronously transmitted to the data transmission module and data storage device. This ensures data quality while reducing the risk of systematic data errors and minimizing production losses caused by sudden failures.

[0054] On the basis of the above embodiments, the sensor calibration module 120 in this embodiment includes a first calibration unit and a second calibration unit. The first calibration unit and the second calibration unit are both installed on industrial equipment and electrically connected to the sensor module 110 .

[0055] The first verification unit is configured with a preset initial verification model. Based on the acquisition time of the sensor module 110, the first verification unit determines an initial verification coefficient in the preset initial verification model. The initial verification coefficient is then used to perform initial verification on the sensor module 110 before multimodal data acquisition. The first verification unit dynamically determines the verification coefficient based on the preset initial verification model and the sensor acquisition time, thereby performing pre-acquisition verification on the sensor. Specifically, the preset initial verification model is trained using historical data to establish a mapping relationship between sensor acquisition time and verification coefficient. For example, the initial verification model can be a linear regression model. The initial verification coefficient is determined by querying the initial verification model based on the current acquisition time and outputting the initial verification coefficient, such as the zero drift compensation value for the temperature sensor. Initial verification can verify that the sensor output is within the allowable error range by applying a standard signal, such as a fixed voltage. This ensures that the sensor is in normal operating condition after power-on, preventing systematic data deviations caused by hardware failures. Furthermore, the verification coefficient is adjusted based on the acquisition time to accommodate sensor aging characteristics over time. This eliminates outliers caused by electromagnetic interference and sensor failures in real time, ensuring data validity.

[0056] The second verification unit is provided with a data comparison model, and the second verification unit confirms the data comparison parameters in the data comparison model based on the initial verification coefficient. The second verification unit performs preliminary data verification on each data in the multimodal data using the data comparison parameters. Among them, the second verification unit is a module that performs real-time verification of multimodal data based on the data comparison model and the initial verification coefficient. The data comparison parameters adjust the threshold range of the data comparison model (such as the allowable deviation of temperature data ±1°C) according to the initial verification coefficient (such as the zero drift compensation value). Then, adaptive verification is achieved through the data comparison model, reducing the workload of manually setting the threshold.

[0057] In this embodiment, the first verification unit determines the calibration coefficient using a preset model, performing pre-collection sensor verification to ensure hardware functionality. The second verification unit generates verification parameters based on the calibration coefficient and performs a triple check of threshold, logic, and model for each data point, significantly improving data quality and system reliability.

[0058] Building on the above embodiment, the sensor calibration module 120 in this embodiment further includes a calibration warning unit. This unit monitors the status of the first calibration unit and triggers a warning and restart operation if the first calibration unit fails calibration. By issuing a warning and automatically restarting the first calibration unit, the unit ensures the continuity and reliability of data collection.

[0059] The verification warning unit is electrically connected to the first verification unit. When the first verification unit fails in the initial verification, the verification warning unit issues a warning prompt and restarts the first verification unit. Industrial equipment has extremely high requirements for the continuity of data acquisition. Verification failure may cause data interruption and affect production. When the first verification unit fails in the initial verification, the verification warning unit will detect a failure signal. The verification warning unit triggers the warning mechanism, such as sending an alarm message to the control center or activating a local alarm. At the same time, the verification warning unit will automatically restart the first verification unit and try to re-calibrate. If multiple restarts fail, further processing may be required, such as switching to a backup sensor for data acquisition or notifying maintenance personnel to maintain the relevant sensors. The verification warning unit ensures the continuity and reliability of data acquisition and reduces data loss or system downtime caused by verification failure. The warning function can promptly notify relevant personnel to prevent potential system failures. The automatic restart mechanism reduces the time for manual troubleshooting and improves maintenance efficiency.

[0060] Building on the above embodiment, this embodiment includes a data aggregation unit within the second verification unit. The data aggregation unit, located within the second verification unit, is a structured processing module responsible for integrating the initial verification results for each data point by time or sensor dimension. The initial verification results include a pass or fail flag and a confidence score.

[0061] The data summary unit is electrically connected to the second verification unit, and the data summary unit is used to summarize each initial verification result after the preliminary verification of the data to obtain verification data. Specifically, by receiving the initial verification result of each data point output by the second verification unit, such as whether the initial verification result of the temperature data is within the allowable deviation range. Sort by timestamp or sensor ID, and generate a summary table containing information such as verification status, parameter threshold and comparison model version. At the same time, it supports classification and summary according to the type of verification result (such as threshold verification failure and logic verification failure) to facilitate subsequent analysis. The verification data contains the summary verification results and the corresponding data to ensure that all data are verified according to a unified standard to avoid data fragmentation caused by decentralized verification.

[0062] Building on the previous embodiment, the data transmission module in this embodiment includes an encryption unit and a transmission unit. Industrial data often involves sensitive information, and the encryption unit encrypts the data to prevent leakage. The transmission unit ensures that the data reaches the remote platform in real time.

[0063] The encryption unit and the transmission unit are both electrically connected to the sensor verification module 120, and the encryption unit is used to encrypt the verification data of the preliminary verification. Specifically, the encryption unit is a module that uses an encryption algorithm to encode the verification data to ensure the confidentiality and integrity of the data during transmission. The encryption unit uses a symmetric encryption algorithm, an asymmetric encryption algorithm or a hash algorithm for encryption. For example, the data is generated into a ciphertext by the encryption unit before transmission, and a hash value is generated at the same time for verification at the receiving end. For example, the data is encrypted using the AES-256-CBC mode and an HMAC-SHA256 signature is attached. By comparing the hash values, it is possible to detect whether tampering has occurred during the transmission process to ensure that the data is trustworthy.

[0064] The transmission unit is used to transmit the encrypted verification data that has been preliminarily verified to the remote processing platform. Among them, the transmission unit is responsible for transmitting the encrypted verification data to the module of the remote platform through the communication protocol, and supports multiple industrial protocols to adapt to different scenarios. The transmission unit selects the protocol according to the network environment, such as the MQTT protocol for low-bandwidth scenarios and the OPC UA protocol for high-security scenarios, to enhance the efficiency of transmission. The transmission unit encapsulates the encrypted data into the format specified by the protocol (such as the PAYLOAD field of MQTT) and adds metadata such as timestamp and device ID. The transmission unit encapsulates the ciphertext into the MQTT protocol format and sends it to the remote processing platform through the TCP / IP network. After receiving the data, the remote platform decrypts and verifies the hash value to perform fault prediction or decision feedback. At the same time, the encrypted data is synchronously stored in the data storage device. Thus, through the collaborative design of encryption and transmission, a safe, efficient and compliant industrial data transmission channel is constructed.

[0065] Based on the above embodiment, the transmission module in this embodiment further includes a data volume monitoring unit, which is electrically connected to the sensor verification module 120. Specifically, the data volume monitoring unit is a module that counts the amount of encrypted and verified data in real time and has built-in data volume threshold judgment logic to trigger the subpacketization operation.

[0066] The data volume monitoring unit is provided with a data volume threshold, and is used to monitor the data volume of the encrypted preliminary verified verification data. The data volume monitoring unit can calculate the total amount of encrypted data in real time using a flow billing algorithm (such as byte accumulation) to achieve data volume statistics.

[0067] If the monitored data volume is greater than the data volume threshold, the data volume monitoring unit will sub-packetize the data volume of the verification data that has been preliminarily verified. Specifically, the data volume monitoring unit compares the current data volume with the data volume threshold, such as 1MB. If the data volume threshold is exceeded, sub-packetization is initiated. Sub-packetization divides the data according to a fixed size (such as 1MB / packet) or a dynamic strategy (such as based on the network MTU value), and adds a sub-packet sequence number and a total number of packets identifier. After sub-packetization, the transmission time of a single packet is shortened, reducing the risk of timeouts due to network congestion. At the same time, it ensures that the data packet complies with the single packet size limit of protocols such as MQTT and OPC UA to avoid rejection by the remote processing platform. At the same time, when packet loss occurs, only the lost packet needs to be retransmitted after sub-packetization, which optimizes the efficiency of packet loss recovery.

[0068] On the basis of the above embodiments, the data storage device described in this embodiment includes a storage unit and a retrieval unit, and the storage unit is electrically connected to the sensor verification module 120, and the storage unit is used to store the verification data of the preliminary verification of the data. Among them, the storage unit is a device or database for persistently storing the verification data of the preliminary verification of the data, and supports structured and unstructured data storage. The storage unit receives the verification data output by the sensor verification module 120 and writes it to a storage medium (such as SSD, distributed file system HDFS) in a preset format (such as CSV or Parquet). Indexes are established according to dimensions such as time, device ID and data type, for example, a time series database such as InfluxDB is created to optimize time series data queries. At the same time, RAID technology or distributed storage (such as Hadoop HDFS) is used to ensure data reliability and prevent data loss due to hardware failure.

[0069] The retrieval unit is electrically connected to the storage unit, and the retrieval unit is used to retrieve the verification data of the preliminary verification of the data in the storage unit. Among them, the retrieval unit is a module that provides a data query interface and supports rapid positioning of target data through conditional screening. Conditional screening includes time, device ID and data type. The retrieval unit receives the query conditions input by the user, such as "device ID = 001, time = 2024-07-29, temperature > 70°C", and converts it into a database query language, such as SQL. Use pre-built indexes (such as time index and device ID index) to quickly locate data and avoid full table scans. The query results are formatted and output according to user requirements, such as JSON or a table. At the same time, paging and sorting are also supported. In this embodiment, the storage unit is used to ensure that the verified data is preserved for a long time to meet the needs of historical data backtracking, fault analysis, etc. of industrial equipment. The retrieval unit avoids manual traversal of massive data through structured queries, thereby improving maintenance efficiency.

[0070] Based on the above embodiments, the remote processing platform in this embodiment includes a data processing module and an anomaly detection module.

[0071] The data processing module is electrically connected to the data transmission module, and the data processing module is used to process the verification data of the preliminary verification. Among them, the data processing module is a module that decrypts, reorganizes, cleans, standardizes and extracts features of the encrypted data transmitted to the remote end, providing high-quality input for anomaly detection. The data processing module receives the encrypted subpacket data, reorganizes the complete data stream by the serial number, and restores the original verification data after decryption. The verification data is cleaned, such as processing missing values, such as interpolation filling, outliers, such as Z-score filtering and correcting format errors, such as timestamp standardization. After cleaning, the missing rate of the data is reduced, and the quality of the obtained data is significantly improved.

[0072] The anomaly detection module is electrically connected to the data processing module and is used to monitor the processed data for anomalies. The anomaly detection module identifies anomaly patterns based on processed data using statistical methods, machine learning models, or deep learning techniques, supporting real-time alarms and root cause analysis. After selecting an existing anomaly detection algorithm, the anomaly detection module analyzes data item by item through a streaming processing framework, marking anomalies such as sudden temperature increases or abnormal vibration spectra. This module integrates knowledge graphs of industrial equipment, such as the relationship between motors, bearings, and lubrication, to trace the root cause of anomalies, such as vibration anomalies caused by bearing failures.

[0073] Based on any of the above industrial equipment data acquisition systems, refer to Figure 3 As shown, the present application also provides an industrial equipment data collection method, comprising the following steps:

[0074] S100: driving the sensor module to collect multimodal data of industrial equipment.

[0075] S200: performing an initial verification on the sensor module before multimodal data collection and performing preliminary data verification on the multimodal data by the sensor verification module to obtain an initial verification result and preliminary verification data.

[0076] S300: Utilize the data transmission module to transmit the preliminary verification data to the remote processing platform.

[0077] S400: Storing verification data of the preliminary data verification in a data storage device.

[0078] In this embodiment, the multimodal data of the industrial equipment is collected through the sensor module, thereby being able to comprehensively monitor the working status of the industrial equipment; the sensor module is initially verified before the multimodal data is collected and the multimodal data is preliminarily verified through the sensor verification module, and the accuracy of the sensor baseline is ensured through the initial verification; at the same time, the preliminary data verification avoids invalid data transmission; the verification data of the preliminary verification is transmitted to the remote processing platform through the data transmission module, and the verification data is processed by the remote processing platform. The verification data of the preliminary data verification is stored through the data storage device; the data storage device is used for local backup or subsequent analysis of the data. When the data transmission module is interrupted, retransmission can be performed, thereby improving the accuracy of data collection; at the same time, the risk of systematic data errors is reduced.

[0079] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0080] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An industrial equipment data acquisition system, characterized in that: include: Sensor modules are installed on industrial equipment to collect multimodal data from the industrial equipment; A sensor calibration module is installed on the industrial equipment and is electrically connected to the sensor module, and is used to perform initial calibration on the sensor module before multimodal data acquisition and to perform preliminary data verification on the multimodal data; a data transmission module, electrically connected to the sensor verification module, for transmitting the verification data of the preliminary verification to a remote processing platform; A data storage device is electrically connected to the sensor verification module and is used to store verification data of preliminary data verification.

2. The industrial equipment data acquisition system according to claim 1, characterized in that: The sensor module includes a sensor unit and a data pre-processing unit, both of which are installed on the industrial equipment, and the sensor unit is electrically connected to the data pre-processing unit; The sensor unit is used to collect multimodal initial data of industrial equipment including images, sounds, temperature and humidity, electrical signals and pressure; The data preprocessing unit is used to preprocess the multimodal initial data to obtain multimodal data.

3. The industrial equipment data acquisition system according to claim 1, characterized in that: The sensor calibration module includes a first calibration unit and a second calibration unit, wherein the first calibration unit and the second calibration unit are both installed on the industrial equipment and are both electrically connected to the sensor module; The first verification unit is provided with a preset initial verification model. After determining an initial verification coefficient in the preset initial verification model based on the acquisition time of the sensor module, the first verification unit uses the initial verification coefficient to perform initial verification on the sensor module before multimodal data acquisition; A data comparison model is provided in the second verification unit. The second verification unit confirms data comparison parameters in the data comparison model based on an initial verification coefficient. The second verification unit performs preliminary data verification on each data in the multimodal data using the data comparison parameters.

4. The industrial equipment data acquisition system according to claim 3, characterized in that: The sensor calibration module also includes a calibration early warning unit; The verification warning unit is electrically connected to the first verification unit. When the first verification unit fails in initial verification, the verification warning unit issues a warning prompt and restarts the first verification unit.

5. The industrial equipment data acquisition system according to claim 3, characterized in that: The second verification unit is provided with a data summarization unit; The data summarizing unit is electrically connected to the second verification unit, and is used to summarize each initial verification result after preliminary verification of the data to obtain verification data.

6. The industrial equipment data acquisition system according to claim 1, characterized in that: The data transmission module includes an encryption unit and a transmission unit; The encryption unit and the transmission unit are both electrically connected to the sensor verification module, and the encryption unit is used to encrypt the verification data of the preliminary verification; The transmission unit is used to transmit the encrypted verification data that will be preliminarily verified to the remote processing platform.

7. The industrial equipment data acquisition system according to claim 6, characterized in that: The transmission module further includes a data volume monitoring unit, which is electrically connected to the sensor verification module; The data volume monitoring unit is provided with a data volume threshold, and the data volume monitoring unit is used to monitor the data volume of the encrypted preliminary verified verification data; If the monitored data volume is greater than the data volume threshold, the data volume monitoring unit sub-packets the data volume of the initially verified verification data.

8. The industrial equipment data acquisition system according to claim 1, characterized in that: The data storage device includes a storage unit and a retrieval unit, the storage unit is electrically connected to the sensor verification module, and the storage unit is used to store verification data of the preliminary data verification; The retrieval unit is electrically connected to the storage unit, and is used to retrieve verification data for preliminary verification of data in the storage unit.

9. The industrial equipment data acquisition system according to claim 1, characterized in that: The remote processing platform includes a data processing module and an anomaly detection module; The data processing module is electrically connected to the data transmission module, and the data processing module is used to process the verification data of the preliminary verification; The anomaly detection module is electrically connected to the data processing module, and the anomaly detection module is used to perform anomaly monitoring on the data after data processing.

10. An industrial equipment data acquisition method, used in the industrial equipment data acquisition system according to any one of claims 1 to 9, characterized in that: The following steps are involved: Drive sensor modules to collect multimodal data from industrial equipment; Performing an initial calibration on the sensor module before multimodal data acquisition and performing preliminary data verification on the multimodal data through the sensor calibration module to obtain an initial calibration result and preliminary verification data; Using the data transmission module to transmit the preliminary verification data to the remote processing platform; The verification data of the preliminary verification of the data is stored by the data storage device.

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